Genetic stock identification of Atlantic salmon and its evaluation in a large population complex

Addressing biocomplexity in fisheries management is a challenge requiring an ability to differentiate between distinct populations contributing to fisheries. We produced extensive genetic baseline data involving 36 sampling locations and 33 microsatellite markers, which allowed characterization of t...

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Main Authors: Vähä, Juha-Pekka, Erkinaro, Jaakko, Fålkegard, Morten, Orell, Panu, Niemelä, Eero
Format: Article in Journal/Newspaper
Language:unknown
Published: NRC Research Press (a division of Canadian Science Publishing) 2016
Subjects:
Online Access:http://hdl.handle.net/1807/73963
http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0606
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spelling ftunivtoronto:oai:localhost:1807/73963 2023-05-15T15:31:38+02:00 Genetic stock identification of Atlantic salmon and its evaluation in a large population complex Vähä, Juha-Pekka Erkinaro, Jaakko Fålkegard, Morten Orell, Panu Niemelä, Eero 2016-07-04 http://hdl.handle.net/1807/73963 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0606 unknown NRC Research Press (a division of Canadian Science Publishing) 0706-652X http://hdl.handle.net/1807/73963 http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0606 Article 2016 ftunivtoronto 2020-06-17T12:00:53Z Addressing biocomplexity in fisheries management is a challenge requiring an ability to differentiate between distinct populations contributing to fisheries. We produced extensive genetic baseline data involving 36 sampling locations and 33 microsatellite markers, which allowed characterization of the genetic structure and diversity in a large Atlantic salmon population complex of the River Teno system, northernmost Europe. Altogether, we identified 28 hierarchically structured and genetically distinct population segments (Global FST = 0.065) corresponding exceptionally well with their geographical locations. An assessment of factors affecting the stock identification accuracy indicated that the identification success is largely defined by the interaction of genetic divergence and the baseline sample sizes. The choice between the two statistical methods tested for performance in genetic stock identification, ONCOR and cBAYES, was not critical, albeit the latter demonstrated slightly higher identification accuracy and lower sensitivity to population composition of the mixture sample. The strong genetic structuring among populations together with a powerful marker system allowed for accurate stock identification of individuals and enabled assessment of stock compositions contributing to mixed stock fisheries. The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author. Article in Journal/Newspaper Atlantic salmon University of Toronto: Research Repository T-Space Teno ENVELOPE(25.690,25.690,68.925,68.925)
institution Open Polar
collection University of Toronto: Research Repository T-Space
op_collection_id ftunivtoronto
language unknown
description Addressing biocomplexity in fisheries management is a challenge requiring an ability to differentiate between distinct populations contributing to fisheries. We produced extensive genetic baseline data involving 36 sampling locations and 33 microsatellite markers, which allowed characterization of the genetic structure and diversity in a large Atlantic salmon population complex of the River Teno system, northernmost Europe. Altogether, we identified 28 hierarchically structured and genetically distinct population segments (Global FST = 0.065) corresponding exceptionally well with their geographical locations. An assessment of factors affecting the stock identification accuracy indicated that the identification success is largely defined by the interaction of genetic divergence and the baseline sample sizes. The choice between the two statistical methods tested for performance in genetic stock identification, ONCOR and cBAYES, was not critical, albeit the latter demonstrated slightly higher identification accuracy and lower sensitivity to population composition of the mixture sample. The strong genetic structuring among populations together with a powerful marker system allowed for accurate stock identification of individuals and enabled assessment of stock compositions contributing to mixed stock fisheries. The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author.
format Article in Journal/Newspaper
author Vähä, Juha-Pekka
Erkinaro, Jaakko
Fålkegard, Morten
Orell, Panu
Niemelä, Eero
spellingShingle Vähä, Juha-Pekka
Erkinaro, Jaakko
Fålkegard, Morten
Orell, Panu
Niemelä, Eero
Genetic stock identification of Atlantic salmon and its evaluation in a large population complex
author_facet Vähä, Juha-Pekka
Erkinaro, Jaakko
Fålkegard, Morten
Orell, Panu
Niemelä, Eero
author_sort Vähä, Juha-Pekka
title Genetic stock identification of Atlantic salmon and its evaluation in a large population complex
title_short Genetic stock identification of Atlantic salmon and its evaluation in a large population complex
title_full Genetic stock identification of Atlantic salmon and its evaluation in a large population complex
title_fullStr Genetic stock identification of Atlantic salmon and its evaluation in a large population complex
title_full_unstemmed Genetic stock identification of Atlantic salmon and its evaluation in a large population complex
title_sort genetic stock identification of atlantic salmon and its evaluation in a large population complex
publisher NRC Research Press (a division of Canadian Science Publishing)
publishDate 2016
url http://hdl.handle.net/1807/73963
http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0606
long_lat ENVELOPE(25.690,25.690,68.925,68.925)
geographic Teno
geographic_facet Teno
genre Atlantic salmon
genre_facet Atlantic salmon
op_relation 0706-652X
http://hdl.handle.net/1807/73963
http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0606
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